Building AI systems designed for measurable business outcomes.

Intel discovered SEO Content AI through organic channels, validated the platform's capabilities, and contracted six-figure for enterprise AI product delivery. This engagement represents Fortune 100 validation of my ability to build production AI systems that meet enterprise requirements.

Led cross-functional team spanning frontend development, data engineering, and DevOps—delivering production-ready AI solution in 9 weeks. Managed stakeholder communication, technical specifications, and milestone delivery under aggressive timeline.

Demonstrated full AI implementation lifecycle: opportunity identification → technical architecture → development coordination → production deployment → business model validation.

Identified market gap for agentic AI tools that could build entire websites from prompts and automate content marketing at scale. Built from scratch with measurement architecture integrated from day one.

Built full-stack AI SaaS platform from scratch: React frontend, AWS backend (Lambda, DynamoDB), integrating Claude, GPT, and Flux AI models. Two core products: agentic website builder that generates complete sites from prompts, and automated content marketing system.

Architected for scale with WebSocket real-time updates, Stripe subscription infrastructure, team management, and Google ecosystem integrations. Achieved thousands of users with zero marketing spend—pure product-market fit validation.

This platform directly led to Fortune 100 engagement: they discovered the product, validated capabilities, and contracted six-figure for enterprise AI delivery.

Robert Half's global web forms required comprehensive testing across 18 countries, multiple languages, and various form types. Traditional testing approaches required extensive manual maintenance, couldn't handle modern Shadow DOM components, and relied on commercial tools with significant licensing costs.

Designed and built the Discovery Framework—a purpose-built automated testing system that dynamically discovers and tests forms without pre-written test cases. Unlike traditional testing that breaks with UI changes, this framework adapts automatically.

Key innovations include native Shadow DOM support for modern web components, network traffic analysis for analytics validation (replacing screenshot-based verification), and process-based parallelization achieving 3-5x faster execution.

The framework validates GA4 and server-side tracking, generates structured logs for Domo dashboards, and integrates with GCP for cloud-based execution. Replaced commercial ObservePoint tooling entirely.